Simplest Explanation of the Standard Errors of Regression Coefficients - Statistics Help

A simple tutorial explaining the standard errors of regression coefficients. This is a step-by-step explanation of the meaning and importance of the standard error.

****

LOOKING FOR AN ONLINE TUTOR?

Are you struggling with statistics or your university studies? I've had several requests for ONLINE TUITION. I highly recommend my colleague Amber who is a gifted online tutor! All her sessions are done via Zoom. I've heard great things from her students, and have seen her teach first hand! Amber is an amazingly talented tutor.

Good luck!! :D

****

*** Check out some of our other mini-lectures:

Ever wondered why we divide by N-1 for sample variance?

Simple Introduction to Hypothesis Testing:

A Simple Rule to Correctly Setting Up the Null and Alternate Hypotheses:

The Easiest Introduction to Regression Analysis:

Super Easy Tutorial on Calculating the Probability of a Type 2 Error:

**

Keywords: statistics, statistics help, statistics tutor, statistics tuition, hypothesis testing, regression analysis, university help, stats help, simple regression, multiple regression, econometrics, standard error, standard error of coefficients, regression coefficients, multiple regression, standard errors

[QuantConceptsE]

Hi my viewers! Are you in need of an online tutor? If so, check out the video description for details 😊

[ridmiratnayake]

Thank you for this simple explanation!

[Msow]

Thank you ! I was so lost and this made it all click

[jiahaoliu]

very informative short revision video, wish you were my lecturer thanks for your videos

[regularviewer]

This video is absolutely fantastic. Thank you very much Dave!

[luhan]

Thank you for the video, this is exactly what I was asked in an interview!

[HansTheCool]

I don't know about this being simple man, this confused me more that I was at the start of the video

[jpedrocmf]

Great video! It was really helpful, thanks!!

[kevinshao]

Thanks for the video! One question: then what distribution and what test should we use to measure the critical score or p-value for regression coefficient?

[mohammadpourheydarian]

A very simple explanation of standard error of beta and t. Thank you.

[xb]

So how can we estimate the standard error of beta hat with only 1 sample? It seems like you need access to mutliple samples to get this info? or do we use sub samples from within our 1 sample that we have?

[rmard]

I have been trying to find how to calculate the standard errors of regression coefficients, but sadly most of the tutorial only show how you can do that with tools (excel, etc.). While I need to create my own program that can the linear regression. Any clue / suggestion?

[AuliaAF]

Then, if we can write mean +- SD, is it similarly logical to write:
y = (Beta +- SE)x + constant
??
Not for actual writing, since it is non-standard. Just want to check if my understanding is correct..

[suri_youtu]

Given that we only supply one data-set(training) to a Regression problem, where does the data for re-sampling and in turn re-estimation of 'beta' come from ? Is the supplied training data assumed to be the population and re-sampled from ?

[p.j.]

Can one use linest to calculate standard error of slope and intercept?

[regivm]

It will be great if you can provide an intuitive explanation of standard errors of coefficients. The title give such an impression.

[AI-ewrj]

How did you calculate how far beta was from 0?

[bratbalal]

Oww why do some don't explain the reason of finding standard error for regression analysis
Thanks

[_Sam_-zhsw]

how does one directly calculates that Beta is 5 standard errors away from 0?

[DRmrTG]

Here's my take:

Suppose that our standard error is 0.2 for an estimate of B, ^B, that = 1. In that case, our estimate is 5 standard errors away from zero, which is what we assume the true B is under the H0. That’s pretty far away from the 0, far enough to suppose that this estimate of 1 is not due to the characteristics of one particular sample. There is a very decent chance that we will be able to reproduce this estimate through another sample.